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<div class="header">
  <div class="summary">
<a href="#pub-methods">Public 成员函数</a> &#124;
<a href="#pri-attribs">Private 属性</a> &#124;
<a href="classpcl_1_1_regression_variance_stats_estimator-members.html">所有成员列表</a>  </div>
  <div class="headertitle">
<div class="title">pcl::RegressionVarianceStatsEstimator&lt; LabelDataType, NodeType, DataSet, ExampleIndex &gt; 模板类 参考</div>  </div>
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<p><a class="el" href="class_statistics.html">Statistics</a> estimator for regression trees which optimizes variance.  
 <a href="classpcl_1_1_regression_variance_stats_estimator.html#details">更多...</a></p>

<p><code>#include &lt;<a class="el" href="regression__variance__stats__estimator_8h_source.html">regression_variance_stats_estimator.h</a>&gt;</code></p>
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类 pcl::RegressionVarianceStatsEstimator&lt; LabelDataType, NodeType, DataSet, ExampleIndex &gt; 继承关系图:</div>
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  <img src="classpcl_1_1_regression_variance_stats_estimator.png" usemap="#pcl::RegressionVarianceStatsEstimator_3C_20LabelDataType_2C_20NodeType_2C_20DataSet_2C_20ExampleIndex_20_3E_map" alt=""/>
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<area href="classpcl_1_1_stats_estimator.html" title="Class interface for gathering statistics for decision tree learning." alt="pcl::StatsEstimator&lt; LabelDataType, NodeType, DataSet, ExampleIndex &gt;" shape="rect" coords="0,0,543,24"/>
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<table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a>
Public 成员函数</h2></td></tr>
<tr class="memitem:a73f69f48a8a6593b47b34f93968cd1a9"><td class="memItemLeft" align="right" valign="top"><a id="a73f69f48a8a6593b47b34f93968cd1a9"></a>
&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_regression_variance_stats_estimator.html#a73f69f48a8a6593b47b34f93968cd1a9">RegressionVarianceStatsEstimator</a> (<a class="el" href="classpcl_1_1_branch_estimator.html">BranchEstimator</a> *branch_estimator)</td></tr>
<tr class="memdesc:a73f69f48a8a6593b47b34f93968cd1a9"><td class="mdescLeft">&#160;</td><td class="mdescRight">Constructor. <br /></td></tr>
<tr class="separator:a73f69f48a8a6593b47b34f93968cd1a9"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a64941b7d4d7e4edd9262b18e4c36937a"><td class="memItemLeft" align="right" valign="top"><a id="a64941b7d4d7e4edd9262b18e4c36937a"></a>
virtual&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_regression_variance_stats_estimator.html#a64941b7d4d7e4edd9262b18e4c36937a">~RegressionVarianceStatsEstimator</a> ()</td></tr>
<tr class="memdesc:a64941b7d4d7e4edd9262b18e4c36937a"><td class="mdescLeft">&#160;</td><td class="mdescRight">Destructor. <br /></td></tr>
<tr class="separator:a64941b7d4d7e4edd9262b18e4c36937a"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ae0a9c3defc64353f7053f4eb63edbc6d"><td class="memItemLeft" align="right" valign="top"><a id="ae0a9c3defc64353f7053f4eb63edbc6d"></a>
size_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_regression_variance_stats_estimator.html#ae0a9c3defc64353f7053f4eb63edbc6d">getNumOfBranches</a> () const</td></tr>
<tr class="memdesc:ae0a9c3defc64353f7053f4eb63edbc6d"><td class="mdescLeft">&#160;</td><td class="mdescRight">Returns the number of branches the corresponding tree has. <br /></td></tr>
<tr class="separator:ae0a9c3defc64353f7053f4eb63edbc6d"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a3701ce301bd5fbd96aa7ee8ce6c2dc29"><td class="memItemLeft" align="right" valign="top">LabelDataType&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_regression_variance_stats_estimator.html#a3701ce301bd5fbd96aa7ee8ce6c2dc29">getLabelOfNode</a> (NodeType &amp;node) const</td></tr>
<tr class="memdesc:a3701ce301bd5fbd96aa7ee8ce6c2dc29"><td class="mdescLeft">&#160;</td><td class="mdescRight">Returns the label of the specified node.  <a href="classpcl_1_1_regression_variance_stats_estimator.html#a3701ce301bd5fbd96aa7ee8ce6c2dc29">更多...</a><br /></td></tr>
<tr class="separator:a3701ce301bd5fbd96aa7ee8ce6c2dc29"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a7c5c4efbb4ac50525954aae8b8389995"><td class="memItemLeft" align="right" valign="top">float&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_regression_variance_stats_estimator.html#a7c5c4efbb4ac50525954aae8b8389995">computeInformationGain</a> (DataSet &amp;data_set, std::vector&lt; ExampleIndex &gt; &amp;examples, std::vector&lt; LabelDataType &gt; &amp;label_data, std::vector&lt; float &gt; &amp;results, std::vector&lt; unsigned char &gt; &amp;flags, const float threshold) const</td></tr>
<tr class="memdesc:a7c5c4efbb4ac50525954aae8b8389995"><td class="mdescLeft">&#160;</td><td class="mdescRight">Computes the information gain obtained by the specified threshold.  <a href="classpcl_1_1_regression_variance_stats_estimator.html#a7c5c4efbb4ac50525954aae8b8389995">更多...</a><br /></td></tr>
<tr class="separator:a7c5c4efbb4ac50525954aae8b8389995"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a5de2e6cbeff519afd171414f66a953aa"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_regression_variance_stats_estimator.html#a5de2e6cbeff519afd171414f66a953aa">computeBranchIndices</a> (std::vector&lt; float &gt; &amp;results, std::vector&lt; unsigned char &gt; &amp;flags, const float threshold, std::vector&lt; unsigned char &gt; &amp;branch_indices) const</td></tr>
<tr class="memdesc:a5de2e6cbeff519afd171414f66a953aa"><td class="mdescLeft">&#160;</td><td class="mdescRight">Computes the branch indices for all supplied results.  <a href="classpcl_1_1_regression_variance_stats_estimator.html#a5de2e6cbeff519afd171414f66a953aa">更多...</a><br /></td></tr>
<tr class="separator:a5de2e6cbeff519afd171414f66a953aa"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a34daa4a214600dca0b200580280633af"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_regression_variance_stats_estimator.html#a34daa4a214600dca0b200580280633af">computeBranchIndex</a> (const float result, const unsigned char flag, const float threshold, unsigned char &amp;branch_index) const</td></tr>
<tr class="memdesc:a34daa4a214600dca0b200580280633af"><td class="mdescLeft">&#160;</td><td class="mdescRight">Computes the branch index for the specified result.  <a href="classpcl_1_1_regression_variance_stats_estimator.html#a34daa4a214600dca0b200580280633af">更多...</a><br /></td></tr>
<tr class="separator:a34daa4a214600dca0b200580280633af"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a269548f1ae1f8c96b27ab71657763393"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_regression_variance_stats_estimator.html#a269548f1ae1f8c96b27ab71657763393">computeAndSetNodeStats</a> (DataSet &amp;data_set, std::vector&lt; ExampleIndex &gt; &amp;examples, std::vector&lt; LabelDataType &gt; &amp;label_data, NodeType &amp;node) const</td></tr>
<tr class="memdesc:a269548f1ae1f8c96b27ab71657763393"><td class="mdescLeft">&#160;</td><td class="mdescRight">Computes and sets the statistics for a node.  <a href="classpcl_1_1_regression_variance_stats_estimator.html#a269548f1ae1f8c96b27ab71657763393">更多...</a><br /></td></tr>
<tr class="separator:a269548f1ae1f8c96b27ab71657763393"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ab5d5128e679e2d1a252e376cf1bf856d"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_regression_variance_stats_estimator.html#ab5d5128e679e2d1a252e376cf1bf856d">generateCodeForBranchIndexComputation</a> (NodeType &amp;node, std::ostream &amp;stream) const</td></tr>
<tr class="memdesc:ab5d5128e679e2d1a252e376cf1bf856d"><td class="mdescLeft">&#160;</td><td class="mdescRight">Generates code for branch index computation.  <a href="classpcl_1_1_regression_variance_stats_estimator.html#ab5d5128e679e2d1a252e376cf1bf856d">更多...</a><br /></td></tr>
<tr class="separator:ab5d5128e679e2d1a252e376cf1bf856d"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a11783c9d3b7e5a81b91b17d290ae4950"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_regression_variance_stats_estimator.html#a11783c9d3b7e5a81b91b17d290ae4950">generateCodeForOutput</a> (NodeType &amp;node, std::ostream &amp;stream) const</td></tr>
<tr class="memdesc:a11783c9d3b7e5a81b91b17d290ae4950"><td class="mdescLeft">&#160;</td><td class="mdescRight">Generates code for label output.  <a href="classpcl_1_1_regression_variance_stats_estimator.html#a11783c9d3b7e5a81b91b17d290ae4950">更多...</a><br /></td></tr>
<tr class="separator:a11783c9d3b7e5a81b91b17d290ae4950"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="inherit_header pub_methods_classpcl_1_1_stats_estimator"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_classpcl_1_1_stats_estimator')"><img src="closed.png" alt="-"/>&#160;Public 成员函数 继承自 <a class="el" href="classpcl_1_1_stats_estimator.html">pcl::StatsEstimator&lt; LabelDataType, NodeType, DataSet, ExampleIndex &gt;</a></td></tr>
<tr class="memitem:aa3ca14fa2a1a43861a0278370b165203 inherit pub_methods_classpcl_1_1_stats_estimator"><td class="memItemLeft" align="right" valign="top"><a id="aa3ca14fa2a1a43861a0278370b165203"></a>
virtual&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_stats_estimator.html#aa3ca14fa2a1a43861a0278370b165203">~StatsEstimator</a> ()</td></tr>
<tr class="memdesc:aa3ca14fa2a1a43861a0278370b165203 inherit pub_methods_classpcl_1_1_stats_estimator"><td class="mdescLeft">&#160;</td><td class="mdescRight">Destructor. <br /></td></tr>
<tr class="separator:aa3ca14fa2a1a43861a0278370b165203 inherit pub_methods_classpcl_1_1_stats_estimator"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pri-attribs"></a>
Private 属性</h2></td></tr>
<tr class="memitem:a6aa8a1cbb16354060dd5800d8f331c1d"><td class="memItemLeft" align="right" valign="top"><a id="a6aa8a1cbb16354060dd5800d8f331c1d"></a>
<a class="el" href="classpcl_1_1_branch_estimator.html">pcl::BranchEstimator</a> *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_regression_variance_stats_estimator.html#a6aa8a1cbb16354060dd5800d8f331c1d">branch_estimator_</a></td></tr>
<tr class="memdesc:a6aa8a1cbb16354060dd5800d8f331c1d"><td class="mdescLeft">&#160;</td><td class="mdescRight">The branch estimator. <br /></td></tr>
<tr class="separator:a6aa8a1cbb16354060dd5800d8f331c1d"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table>
<a name="details" id="details"></a><h2 class="groupheader">详细描述</h2>
<div class="textblock"><h3>template&lt;class LabelDataType, class NodeType, class DataSet, class ExampleIndex&gt;<br />
class pcl::RegressionVarianceStatsEstimator&lt; LabelDataType, NodeType, DataSet, ExampleIndex &gt;</h3>

<p><a class="el" href="class_statistics.html">Statistics</a> estimator for regression trees which optimizes variance. </p>
</div><h2 class="groupheader">成员函数说明</h2>
<a id="a269548f1ae1f8c96b27ab71657763393"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a269548f1ae1f8c96b27ab71657763393">&#9670;&nbsp;</a></span>computeAndSetNodeStats()</h2>

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<div class="memtemplate">
template&lt;class LabelDataType , class NodeType , class DataSet , class ExampleIndex &gt; </div>
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">void <a class="el" href="classpcl_1_1_regression_variance_stats_estimator.html">pcl::RegressionVarianceStatsEstimator</a>&lt; LabelDataType, NodeType, DataSet, ExampleIndex &gt;::computeAndSetNodeStats </td>
          <td>(</td>
          <td class="paramtype">DataSet &amp;&#160;</td>
          <td class="paramname"><em>data_set</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">std::vector&lt; ExampleIndex &gt; &amp;&#160;</td>
          <td class="paramname"><em>examples</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">std::vector&lt; LabelDataType &gt; &amp;&#160;</td>
          <td class="paramname"><em>label_data</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">NodeType &amp;&#160;</td>
          <td class="paramname"><em>node</em>&#160;</td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td> const</td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">inline</span><span class="mlabel">virtual</span></span>  </td>
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</div><div class="memdoc">

<p>Computes and sets the statistics for a node. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">data_set</td><td>The data set which is evaluated. </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">examples</td><td>The examples which define which parts of the data set are used for evaluation. </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">label_data</td><td>The label_data corresponding to the examples. </td></tr>
    <tr><td class="paramdir">[out]</td><td class="paramname">node</td><td>The destination node for the statistics. </td></tr>
  </table>
  </dd>
</dl>

<p>实现了 <a class="el" href="classpcl_1_1_stats_estimator.html#a6caa1bf87f7cb0b697d4fc081f0339af">pcl::StatsEstimator&lt; LabelDataType, NodeType, DataSet, ExampleIndex &gt;</a>.</p>
<div class="fragment"><div class="line"><a name="l00276"></a><span class="lineno">  276</span>&#160;      {</div>
<div class="line"><a name="l00277"></a><span class="lineno">  277</span>&#160;        <span class="keyword">const</span> <span class="keywordtype">size_t</span> num_of_examples = examples.size ();</div>
<div class="line"><a name="l00278"></a><span class="lineno">  278</span>&#160; </div>
<div class="line"><a name="l00279"></a><span class="lineno">  279</span>&#160;        LabelDataType sum = 0.0f;</div>
<div class="line"><a name="l00280"></a><span class="lineno">  280</span>&#160;        LabelDataType sqr_sum = 0.0f;</div>
<div class="line"><a name="l00281"></a><span class="lineno">  281</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> example_index = 0; example_index &lt; num_of_examples; ++example_index)</div>
<div class="line"><a name="l00282"></a><span class="lineno">  282</span>&#160;        {</div>
<div class="line"><a name="l00283"></a><span class="lineno">  283</span>&#160;          <span class="keyword">const</span> LabelDataType label = label_data[example_index];</div>
<div class="line"><a name="l00284"></a><span class="lineno">  284</span>&#160; </div>
<div class="line"><a name="l00285"></a><span class="lineno">  285</span>&#160;          sum += label;</div>
<div class="line"><a name="l00286"></a><span class="lineno">  286</span>&#160;          sqr_sum += label*label;</div>
<div class="line"><a name="l00287"></a><span class="lineno">  287</span>&#160;        }</div>
<div class="line"><a name="l00288"></a><span class="lineno">  288</span>&#160; </div>
<div class="line"><a name="l00289"></a><span class="lineno">  289</span>&#160;        sum /= num_of_examples;</div>
<div class="line"><a name="l00290"></a><span class="lineno">  290</span>&#160;        sqr_sum /= num_of_examples;</div>
<div class="line"><a name="l00291"></a><span class="lineno">  291</span>&#160; </div>
<div class="line"><a name="l00292"></a><span class="lineno">  292</span>&#160;        <span class="keyword">const</span> <span class="keywordtype">float</span> variance = sqr_sum - sum*sum;</div>
<div class="line"><a name="l00293"></a><span class="lineno">  293</span>&#160; </div>
<div class="line"><a name="l00294"></a><span class="lineno">  294</span>&#160;        node.value = sum;</div>
<div class="line"><a name="l00295"></a><span class="lineno">  295</span>&#160;        node.variance = variance;</div>
<div class="line"><a name="l00296"></a><span class="lineno">  296</span>&#160;      }</div>
</div><!-- fragment -->
</div>
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<a id="a34daa4a214600dca0b200580280633af"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a34daa4a214600dca0b200580280633af">&#9670;&nbsp;</a></span>computeBranchIndex()</h2>

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template&lt;class LabelDataType , class NodeType , class DataSet , class ExampleIndex &gt; </div>
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          <td class="memname">void <a class="el" href="classpcl_1_1_regression_variance_stats_estimator.html">pcl::RegressionVarianceStatsEstimator</a>&lt; LabelDataType, NodeType, DataSet, ExampleIndex &gt;::computeBranchIndex </td>
          <td>(</td>
          <td class="paramtype">const float&#160;</td>
          <td class="paramname"><em>result</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const unsigned char&#160;</td>
          <td class="paramname"><em>flag</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const float&#160;</td>
          <td class="paramname"><em>threshold</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">unsigned char &amp;&#160;</td>
          <td class="paramname"><em>branch_index</em>&#160;</td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td> const</td>
        </tr>
      </table>
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<span class="mlabels"><span class="mlabel">inline</span><span class="mlabel">virtual</span></span>  </td>
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<p>Computes the branch index for the specified result. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">result</td><td>The result the branch index will be computed for. </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">flag</td><td>The flag corresponding to the specified result. </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">threshold</td><td>The threshold used to compute the branch index. </td></tr>
    <tr><td class="paramdir">[out]</td><td class="paramname">branch_index</td><td>The destination for the computed branch index. </td></tr>
  </table>
  </dd>
</dl>

<p>实现了 <a class="el" href="classpcl_1_1_stats_estimator.html#ae91303f940dffa974c8f980fa8736426">pcl::StatsEstimator&lt; LabelDataType, NodeType, DataSet, ExampleIndex &gt;</a>.</p>
<div class="fragment"><div class="line"><a name="l00259"></a><span class="lineno">  259</span>&#160;      {</div>
<div class="line"><a name="l00260"></a><span class="lineno">  260</span>&#160;        <a class="code" href="classpcl_1_1_regression_variance_stats_estimator.html#a6aa8a1cbb16354060dd5800d8f331c1d">branch_estimator_</a>-&gt;<a class="code" href="classpcl_1_1_branch_estimator.html#a595a4e2ddc742910336912ff66c6feba">computeBranchIndex</a> (result, flag, threshold, branch_index);</div>
<div class="line"><a name="l00261"></a><span class="lineno">  261</span>&#160;        <span class="comment">//branch_index = (result &gt; threshold) ? 1 : 0;</span></div>
<div class="line"><a name="l00262"></a><span class="lineno">  262</span>&#160;      }</div>
<div class="ttc" id="aclasspcl_1_1_branch_estimator_html_a595a4e2ddc742910336912ff66c6feba"><div class="ttname"><a href="classpcl_1_1_branch_estimator.html#a595a4e2ddc742910336912ff66c6feba">pcl::BranchEstimator::computeBranchIndex</a></div><div class="ttdeci">virtual void computeBranchIndex(const float result, const unsigned char flag, const float threshold, unsigned char &amp;branch_index) const =0</div><div class="ttdoc">Computes the branch index for the specified result.</div></div>
<div class="ttc" id="aclasspcl_1_1_regression_variance_stats_estimator_html_a6aa8a1cbb16354060dd5800d8f331c1d"><div class="ttname"><a href="classpcl_1_1_regression_variance_stats_estimator.html#a6aa8a1cbb16354060dd5800d8f331c1d">pcl::RegressionVarianceStatsEstimator::branch_estimator_</a></div><div class="ttdeci">pcl::BranchEstimator * branch_estimator_</div><div class="ttdoc">The branch estimator.</div><div class="ttdef"><b>Definition:</b> regression_variance_stats_estimator.h:324</div></div>
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<h2 class="memtitle"><span class="permalink"><a href="#a5de2e6cbeff519afd171414f66a953aa">&#9670;&nbsp;</a></span>computeBranchIndices()</h2>

<div class="memitem">
<div class="memproto">
<div class="memtemplate">
template&lt;class LabelDataType , class NodeType , class DataSet , class ExampleIndex &gt; </div>
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
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          <td class="memname">void <a class="el" href="classpcl_1_1_regression_variance_stats_estimator.html">pcl::RegressionVarianceStatsEstimator</a>&lt; LabelDataType, NodeType, DataSet, ExampleIndex &gt;::computeBranchIndices </td>
          <td>(</td>
          <td class="paramtype">std::vector&lt; float &gt; &amp;&#160;</td>
          <td class="paramname"><em>results</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">std::vector&lt; unsigned char &gt; &amp;&#160;</td>
          <td class="paramname"><em>flags</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const float&#160;</td>
          <td class="paramname"><em>threshold</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">std::vector&lt; unsigned char &gt; &amp;&#160;</td>
          <td class="paramname"><em>branch_indices</em>&#160;</td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td> const</td>
        </tr>
      </table>
  </td>
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<span class="mlabels"><span class="mlabel">inline</span><span class="mlabel">virtual</span></span>  </td>
  </tr>
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</div><div class="memdoc">

<p>Computes the branch indices for all supplied results. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">results</td><td>The results the branch indices will be computed for. </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">flags</td><td>The flags corresponding to the specified results. </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">threshold</td><td>The threshold used to compute the branch indices. </td></tr>
    <tr><td class="paramdir">[out]</td><td class="paramname">branch_indices</td><td>The destination for the computed branch indices. </td></tr>
  </table>
  </dd>
</dl>

<p>实现了 <a class="el" href="classpcl_1_1_stats_estimator.html#aa3fda8a830fbaded719ac28b2d6667bb">pcl::StatsEstimator&lt; LabelDataType, NodeType, DataSet, ExampleIndex &gt;</a>.</p>
<div class="fragment"><div class="line"><a name="l00234"></a><span class="lineno">  234</span>&#160;      {</div>
<div class="line"><a name="l00235"></a><span class="lineno">  235</span>&#160;        <span class="keyword">const</span> <span class="keywordtype">size_t</span> num_of_results = results.size ();</div>
<div class="line"><a name="l00236"></a><span class="lineno">  236</span>&#160;        <span class="keyword">const</span> <span class="keywordtype">size_t</span> num_of_branches = <a class="code" href="classpcl_1_1_regression_variance_stats_estimator.html#ae0a9c3defc64353f7053f4eb63edbc6d">getNumOfBranches</a>();</div>
<div class="line"><a name="l00237"></a><span class="lineno">  237</span>&#160; </div>
<div class="line"><a name="l00238"></a><span class="lineno">  238</span>&#160;        branch_indices.resize (num_of_results);</div>
<div class="line"><a name="l00239"></a><span class="lineno">  239</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> result_index = 0; result_index &lt; num_of_results; ++result_index)</div>
<div class="line"><a name="l00240"></a><span class="lineno">  240</span>&#160;        {</div>
<div class="line"><a name="l00241"></a><span class="lineno">  241</span>&#160;          <span class="keywordtype">unsigned</span> <span class="keywordtype">char</span> branch_index;</div>
<div class="line"><a name="l00242"></a><span class="lineno">  242</span>&#160;          <a class="code" href="classpcl_1_1_regression_variance_stats_estimator.html#a34daa4a214600dca0b200580280633af">computeBranchIndex</a> (results[result_index], flags[result_index], threshold, branch_index);</div>
<div class="line"><a name="l00243"></a><span class="lineno">  243</span>&#160;          branch_indices[result_index] = branch_index;</div>
<div class="line"><a name="l00244"></a><span class="lineno">  244</span>&#160;        }</div>
<div class="line"><a name="l00245"></a><span class="lineno">  245</span>&#160;      }</div>
<div class="ttc" id="aclasspcl_1_1_regression_variance_stats_estimator_html_a34daa4a214600dca0b200580280633af"><div class="ttname"><a href="classpcl_1_1_regression_variance_stats_estimator.html#a34daa4a214600dca0b200580280633af">pcl::RegressionVarianceStatsEstimator::computeBranchIndex</a></div><div class="ttdeci">void computeBranchIndex(const float result, const unsigned char flag, const float threshold, unsigned char &amp;branch_index) const</div><div class="ttdoc">Computes the branch index for the specified result.</div><div class="ttdef"><b>Definition:</b> regression_variance_stats_estimator.h:254</div></div>
<div class="ttc" id="aclasspcl_1_1_regression_variance_stats_estimator_html_ae0a9c3defc64353f7053f4eb63edbc6d"><div class="ttname"><a href="classpcl_1_1_regression_variance_stats_estimator.html#ae0a9c3defc64353f7053f4eb63edbc6d">pcl::RegressionVarianceStatsEstimator::getNumOfBranches</a></div><div class="ttdeci">size_t getNumOfBranches() const</div><div class="ttdoc">Returns the number of branches the corresponding tree has.</div><div class="ttdef"><b>Definition:</b> regression_variance_stats_estimator.h:139</div></div>
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<h2 class="memtitle"><span class="permalink"><a href="#a7c5c4efbb4ac50525954aae8b8389995">&#9670;&nbsp;</a></span>computeInformationGain()</h2>

<div class="memitem">
<div class="memproto">
<div class="memtemplate">
template&lt;class LabelDataType , class NodeType , class DataSet , class ExampleIndex &gt; </div>
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">float <a class="el" href="classpcl_1_1_regression_variance_stats_estimator.html">pcl::RegressionVarianceStatsEstimator</a>&lt; LabelDataType, NodeType, DataSet, ExampleIndex &gt;::computeInformationGain </td>
          <td>(</td>
          <td class="paramtype">DataSet &amp;&#160;</td>
          <td class="paramname"><em>data_set</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">std::vector&lt; ExampleIndex &gt; &amp;&#160;</td>
          <td class="paramname"><em>examples</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">std::vector&lt; LabelDataType &gt; &amp;&#160;</td>
          <td class="paramname"><em>label_data</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">std::vector&lt; float &gt; &amp;&#160;</td>
          <td class="paramname"><em>results</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">std::vector&lt; unsigned char &gt; &amp;&#160;</td>
          <td class="paramname"><em>flags</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const float&#160;</td>
          <td class="paramname"><em>threshold</em>&#160;</td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td> const</td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">inline</span><span class="mlabel">virtual</span></span>  </td>
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<p>Computes the information gain obtained by the specified threshold. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">data_set</td><td>The data set corresponding to the supplied result data. </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">examples</td><td>The examples used for extracting the supplied result data. </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">label_data</td><td>The label data corresponding to the specified examples. </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">results</td><td>The results computed using the specifed examples. </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">flags</td><td>The flags corresponding to the results. </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">threshold</td><td>The threshold for which the information gain is computed. </td></tr>
  </table>
  </dd>
</dl>

<p>实现了 <a class="el" href="classpcl_1_1_stats_estimator.html#a4794b4417d32e2844bb137ce7934f905">pcl::StatsEstimator&lt; LabelDataType, NodeType, DataSet, ExampleIndex &gt;</a>.</p>
<div class="fragment"><div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;      {</div>
<div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;        <span class="keyword">const</span> <span class="keywordtype">size_t</span> num_of_examples = examples.size ();</div>
<div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;        <span class="keyword">const</span> <span class="keywordtype">size_t</span> num_of_branches = <a class="code" href="classpcl_1_1_regression_variance_stats_estimator.html#ae0a9c3defc64353f7053f4eb63edbc6d">getNumOfBranches</a>();</div>
<div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160; </div>
<div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160;        <span class="comment">// compute variance</span></div>
<div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;        std::vector&lt;LabelDataType&gt; sums (num_of_branches+1, 0);</div>
<div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;        std::vector&lt;LabelDataType&gt; sqr_sums (num_of_branches+1, 0);</div>
<div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;        std::vector&lt;size_t&gt; branch_element_count (num_of_branches+1, 0);</div>
<div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160; </div>
<div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> branch_index = 0; branch_index &lt; num_of_branches; ++branch_index)</div>
<div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;        {</div>
<div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;          branch_element_count[branch_index] = 1;</div>
<div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;          ++branch_element_count[num_of_branches];</div>
<div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;        }</div>
<div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160; </div>
<div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> example_index = 0; example_index &lt; num_of_examples; ++example_index)</div>
<div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;        {</div>
<div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;          <span class="keywordtype">unsigned</span> <span class="keywordtype">char</span> branch_index;</div>
<div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;          <a class="code" href="classpcl_1_1_regression_variance_stats_estimator.html#a34daa4a214600dca0b200580280633af">computeBranchIndex</a> (results[example_index], flags[example_index], threshold, branch_index);</div>
<div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160; </div>
<div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;          LabelDataType label = label_data[example_index];</div>
<div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160; </div>
<div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;          sums[branch_index] += label;</div>
<div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;          sums[num_of_branches] += label;</div>
<div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160; </div>
<div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;          sqr_sums[branch_index] += label*label;</div>
<div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;          sqr_sums[num_of_branches] += label*label;</div>
<div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160; </div>
<div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;          ++branch_element_count[branch_index];</div>
<div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;          ++branch_element_count[num_of_branches];</div>
<div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;        }</div>
<div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160; </div>
<div class="line"><a name="l00203"></a><span class="lineno">  203</span>&#160;        std::vector&lt;float&gt; variances (num_of_branches+1, 0);</div>
<div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> branch_index = 0; branch_index &lt; num_of_branches+1; ++branch_index)</div>
<div class="line"><a name="l00205"></a><span class="lineno">  205</span>&#160;        {</div>
<div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;          <span class="keyword">const</span> <span class="keywordtype">float</span> mean_sum = <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span>(sums[branch_index]) / branch_element_count[branch_index];</div>
<div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;          <span class="keyword">const</span> <span class="keywordtype">float</span> mean_sqr_sum = <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span>(sqr_sums[branch_index]) / branch_element_count[branch_index];</div>
<div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;          variances[branch_index] = mean_sqr_sum - mean_sum*mean_sum;</div>
<div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;        }</div>
<div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160; </div>
<div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160;        <span class="keywordtype">float</span> information_gain = variances[num_of_branches];</div>
<div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> branch_index = 0; branch_index &lt; num_of_branches; ++branch_index)</div>
<div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160;        {</div>
<div class="line"><a name="l00214"></a><span class="lineno">  214</span>&#160;          <span class="comment">//const float weight = static_cast&lt;float&gt;(sums[branchIndex]) / sums[numOfBranches];</span></div>
<div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160;          <span class="keyword">const</span> <span class="keywordtype">float</span> weight = <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span>(branch_element_count[branch_index]) / <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span>(branch_element_count[num_of_branches]);</div>
<div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160;          information_gain -= weight*variances[branch_index];</div>
<div class="line"><a name="l00217"></a><span class="lineno">  217</span>&#160;        }</div>
<div class="line"><a name="l00218"></a><span class="lineno">  218</span>&#160; </div>
<div class="line"><a name="l00219"></a><span class="lineno">  219</span>&#160;        <span class="keywordflow">return</span> information_gain;</div>
<div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;      }</div>
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<h2 class="memtitle"><span class="permalink"><a href="#ab5d5128e679e2d1a252e376cf1bf856d">&#9670;&nbsp;</a></span>generateCodeForBranchIndexComputation()</h2>

<div class="memitem">
<div class="memproto">
<div class="memtemplate">
template&lt;class LabelDataType , class NodeType , class DataSet , class ExampleIndex &gt; </div>
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">void <a class="el" href="classpcl_1_1_regression_variance_stats_estimator.html">pcl::RegressionVarianceStatsEstimator</a>&lt; LabelDataType, NodeType, DataSet, ExampleIndex &gt;::generateCodeForBranchIndexComputation </td>
          <td>(</td>
          <td class="paramtype">NodeType &amp;&#160;</td>
          <td class="paramname"><em>node</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">std::ostream &amp;&#160;</td>
          <td class="paramname"><em>stream</em>&#160;</td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td> const</td>
        </tr>
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  </td>
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<p>Generates code for branch index computation. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">node</td><td>The node for which code is generated. </td></tr>
    <tr><td class="paramdir">[out]</td><td class="paramname">stream</td><td>The destination for the generated code. </td></tr>
  </table>
  </dd>
</dl>

<p>实现了 <a class="el" href="classpcl_1_1_stats_estimator.html#a66add9942c6d8ae7b911574d5ac1fe19">pcl::StatsEstimator&lt; LabelDataType, NodeType, DataSet, ExampleIndex &gt;</a>.</p>
<div class="fragment"><div class="line"><a name="l00306"></a><span class="lineno">  306</span>&#160;      {</div>
<div class="line"><a name="l00307"></a><span class="lineno">  307</span>&#160;        stream &lt;&lt; <span class="stringliteral">&quot;ERROR: RegressionVarianceStatsEstimator does not implement generateCodeForBranchIndex(...)&quot;</span>;</div>
<div class="line"><a name="l00308"></a><span class="lineno">  308</span>&#160;      }</div>
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</div>
<a id="a11783c9d3b7e5a81b91b17d290ae4950"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a11783c9d3b7e5a81b91b17d290ae4950">&#9670;&nbsp;</a></span>generateCodeForOutput()</h2>

<div class="memitem">
<div class="memproto">
<div class="memtemplate">
template&lt;class LabelDataType , class NodeType , class DataSet , class ExampleIndex &gt; </div>
<table class="mlabels">
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  <td class="mlabels-left">
      <table class="memname">
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          <td class="memname">void <a class="el" href="classpcl_1_1_regression_variance_stats_estimator.html">pcl::RegressionVarianceStatsEstimator</a>&lt; LabelDataType, NodeType, DataSet, ExampleIndex &gt;::generateCodeForOutput </td>
          <td>(</td>
          <td class="paramtype">NodeType &amp;&#160;</td>
          <td class="paramname"><em>node</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">std::ostream &amp;&#160;</td>
          <td class="paramname"><em>stream</em>&#160;</td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td> const</td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">inline</span><span class="mlabel">virtual</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

<p>Generates code for label output. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">node</td><td>The node for which code is generated. </td></tr>
    <tr><td class="paramdir">[out]</td><td class="paramname">stream</td><td>The destination for the generated code. </td></tr>
  </table>
  </dd>
</dl>

<p>实现了 <a class="el" href="classpcl_1_1_stats_estimator.html#a4c3efd505d6c8e711522a3d4e2da60fb">pcl::StatsEstimator&lt; LabelDataType, NodeType, DataSet, ExampleIndex &gt;</a>.</p>
<div class="fragment"><div class="line"><a name="l00318"></a><span class="lineno">  318</span>&#160;      {</div>
<div class="line"><a name="l00319"></a><span class="lineno">  319</span>&#160;        stream &lt;&lt; <span class="stringliteral">&quot;ERROR: RegressionVarianceStatsEstimator does not implement generateCodeForBranchIndex(...)&quot;</span>;</div>
<div class="line"><a name="l00320"></a><span class="lineno">  320</span>&#160;      }</div>
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</div>
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<a id="a3701ce301bd5fbd96aa7ee8ce6c2dc29"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a3701ce301bd5fbd96aa7ee8ce6c2dc29">&#9670;&nbsp;</a></span>getLabelOfNode()</h2>

<div class="memitem">
<div class="memproto">
<div class="memtemplate">
template&lt;class LabelDataType , class NodeType , class DataSet , class ExampleIndex &gt; </div>
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">LabelDataType <a class="el" href="classpcl_1_1_regression_variance_stats_estimator.html">pcl::RegressionVarianceStatsEstimator</a>&lt; LabelDataType, NodeType, DataSet, ExampleIndex &gt;::getLabelOfNode </td>
          <td>(</td>
          <td class="paramtype">NodeType &amp;&#160;</td>
          <td class="paramname"><em>node</em></td><td>)</td>
          <td> const</td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">inline</span><span class="mlabel">virtual</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

<p>Returns the label of the specified node. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">node</td><td>The node which label is returned. </td></tr>
  </table>
  </dd>
</dl>

<p>实现了 <a class="el" href="classpcl_1_1_stats_estimator.html#a81eeb44edc44226e45e9559b8c6adf03">pcl::StatsEstimator&lt; LabelDataType, NodeType, DataSet, ExampleIndex &gt;</a>.</p>
<div class="fragment"><div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;      {</div>
<div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;        <span class="keywordflow">return</span> node.value;</div>
<div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;      }</div>
</div><!-- fragment -->
</div>
</div>
<hr/>该类的文档由以下文件生成:<ul>
<li>ml/include/pcl/ml/<a class="el" href="regression__variance__stats__estimator_8h_source.html">regression_variance_stats_estimator.h</a></li>
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